Abstract: To train a computer vision model to classify health test kit results, a computing system obtains a plurality of training images. Each training image depicts a plurality of health test results in respective segments of a test membrane of a health test kit. The computing system obtains, for each training image, labeling indicating the health test results depicted by the training image. The computing system trains a plurality of local Convolutional Neural Networks (CNNs) of the computer vision model in parallel. Each of the local CNNs is trained to predict the health test result depicted in a respective one of the segments based on local features extracted by the local CNN from the respective one of the segments of each training image and global features extracted by a global CNN of the computer vision model from the test membrane of each training image.

Abstract: Digital data are communicated between a portable data-gathering unit and a data-receiving unit without direct electrical connection by transmitting the data over a contactless connection system. In a preferred embodiment, data flow is bidirectional.